How to detect illegal corporate insider trading? A data mining approach for detecting suspicious insider transactions

• DOI: http://doi.org/10.1002/isaf.1446
• Author: Ulkem Basdas,M. Fevzi Esen,Emrah Bilgic
• Published date: 01 April 2019
• Date: 01 April 2019

RESEARCH ARTICLE

How to detect illegal corporate insider trading? A data mining

approach for detecting suspicious insider transactions

M. Fevzi Esen

1

|Emrah Bilgic

2

|Ulkem Basdas

3

1

Istanbul Medeniyet University, Istanbul,

Turkey

2

Kayseri University, Kayseri, Turkey

3

Philip Morris International, Izmir, Turkey

Correspondence

Esen, M. Fevzi, Istanbul Medeniyet University,

Istanbul, Turkey

Email: fevzi.esen@medeniyet.edu.tr

Summary

Only in the U.S. Stock Exchanges, the daily average trading volume is about 7 bil-

lion shares. This vast amount of trading shows the necessity of understanding the

hidden insights in the data sets. In this study, a data mining technique, clustering

based outlier analysis is applied to detect suspicious insider transactions.

1,244,815 transactions of 61,780 insiders are analysed, which are acquired from

Thomson Financial, covering a period of January 2010–April 2017. In order to

detect outliers, similar transactions are grouped into the same clusters by using a

two‐step clustering based outlier detection technique, which is an integration of

k‐means and hierarchical clustering. Then, it is shown that outlying transactions

earn higher abnormal returns than non‐outlying transactions by using event study

methodology.

KEYWORDS

Corporate InsiderTrading, Event Study, Fraud Detection, Outlier Analysis

1|INTRODUCTION

CEOs, directors, managers and other executive members, those who

are required to disclose their transactions to the public, are a class of

corporate insiders accessing inside information of a company. Corpo-

rate insiders are required to report their transactions in their own firms

following the transaction. Therefore, the stock returns of their transac-

tions are widely studied in the literature. Early researches focused more

on the empirical background of corporate insider transactions and

descriptive findings. In general, these studies suggest that corporate

insiders were willing to exploit their preferential and superior access

to non‐public information in order to get unfair informational advantage

over the market. Besides, the profits generated by insiders (i.e., the

returns of these trades) were found statistically significant (Lakonishok

& Lee, 2001; Lin & Howe, 1990; Marin & Olivier, 2008; Seyhun, 1986).

These researches confirmed that corporate insider trading is informa-

tive and corporate insiders gain higher returns than the market.

Despite the proved informativeness of insider trading, insiders

make their trades for a variety of reasons. Traders, who do not have

any preferential access to inside information and trade for liquidity

or some other reasons, are associated with informational disadvantage

against informed corporate insiders. The uninformed traders (i.e., out-

siders) must ascertain whether insider transactions are privileged of

possession of inside information that would affect the firm value.

Therefore, the classification of information content of an insider trad-

ing is also critical to drive conclusions.

There are specific kinds of corporate insider transactions that have

been prohibited by the law. Insider ‐Trading Sanctions Act of 1984

and Insider ‐Trading and Securities Fraud Enforcement Act of 1988

define illegal insider trading as “buying or selling securities by insiders,

while in possession of material, non‐public information which is not avail-

able to the public”(SEC, 2018). Martha Stewart's stock trading on pref-

erential information and Levine & Boesky's misappropriation of

material, non‐public information about firms for the purpose of

profiting are high‐profile cases of people, who were convicted of

engaging in illegal insider trading.

The presence of abnormal returns from corporate insider transac-

tions shows that insiders use preferential information to conduct prof-

itable trades and they perform significantly better than market. If

insiders' transactions contain predictive content for future returns,

we would expect to see significant abnormal returns (Seyhun, 2000;

Tavakoli, McMillan, & McKnight, 2012).

Received: 7 August 2018 Revised: 15 April 2019 Accepted: 23 April 2019

DOI: 10.1002/isaf.1446

60 © 2019 John Wiley & Sons, Ltd. Intell Sys Acc Fin Mgmt. 2019;26:60–70.wileyonlinelibrary.com/journal/isaf